Make videos on the computer you already own. FreeVideo runs MiniMax H3 in as little as 8 GB of VRAM and 16 GB of RAM, and adapts its acceleration path to your hardware.
Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.
Run many AI agents at once on your Mac, about three times faster.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
SparkDiffusion: Accelerating DiT video generation by 265× via joint Sparsity, Distillation, Quantization, etc.
A Python framework for GPU-accelerated simulation, robotics, and machine learning.
A highly efficient implementation of Gaussian Processes in PyTorch
Brevitas: neural network quantization in PyTorch
LLM model quantization (compression) toolkit with HW acceleration support for Nvidia, AMD, Intel GPU and Intel/AMD/Apple CPU via HF, vLLM, and SGLang.
⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.
Free, open-source, 100% offline voice dictation for Linux. Speak and type anywhere via whisper.cpp, Whisper & VOSK engines, GPU-accelerated, works on X11 + Wayland!
a free local self hosted video compressor webui designed for performance and ease of use. inspired by 8mb.video
Open data and scalable training for long-horizon video world models.
Fresh builds of llama.cpp with AMD ROCm™ 7 acceleration
PypelineC: A hardware description language (HDL) adding high level synthesis(HLS)-like automatic pipelining as a language construct/compiler feature.
Training-free Spectrum acceleration for ComfyUI’s native MiniMax H3 audio-video model. Uses Chebyshev ridge feature forecasting to skip selected H3 transformer evaluations, with adaptive scheduling, sampler-aware support for Euler, ER-SDE, RES, SEEDS and SA-Solver, CPU/VRAM history storage, and fail-closed native fallbacks.
SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse–Linear Attention
Inclusive model of expression dynamics with conventional or metabolic labeling based scRNA-seq / multiomics, vector field reconstruction and differential geometry analyses
A unified, torch-native training framework for MTP and block-parallel speculative decoding.
Local JavaScript + FastAPI video restoration studio for SeedVR2 with TensorRT acceleration, previews, synchronized comparisons, resumable renders, and post-processing.
[ECCV 2026] Official implementation of "HRDiT: Training-Free High-Resolution Image Generation with Off-the-Shelf Diffusion Transformer Models"
MiniMax H3 Ref2VA acceleration for ComfyUI on an RTX 4070 12GB: 4-bit FC1 weights + Streaming VSA sparse attention. 1024x1792 video with audio in about 3 min 17 s, about 3.4x faster than dense attention.
MiniMax-H3 multi-GPU inference acceleration: ~12x on 8x RTX 6000D (step distillation + SageAttention2 + Cache-DiT + torch.compile, TP2+Ulysses4 on sglang)
Lightweight FirstBlockCache acceleration node for native ComfyUI MiniMax H3
Sparse acceleration and LoRA fine-tuning of MiniMax-H3 on resource-constrained machines.
Native MiniMax-H3 inference acceleration for ComfyUI, integrating Exact Runtime optimizations with Sana Sol-Attn, rectangular Q/KV attention, and composable support for VDN, Spectrum, Untwisting RoPE, Diff-Aid, and Flow mixed-grid workflows.
Mixed-precision acceleration patch for MiniMax H3 inference on NVIDIA V100
TaoMate-H3 3-step acceleration package for ComfyUI on an RTX 4070 12GB: 4-bit (W4A4) FFN weights, 10% sparse attention and extra INT8 weight caching, with Windows setup and sample workflows.
应用软件(网络工具) · GitHub 访问优化助手,只在本机分流、退出即还原
ComfyUI nodes for MiniMax H3: INT8 X2 VAE and asynchronous NVENC saving. 5-second 1088x1920 video with audio in about 60 s on an RTX 4070 12GB, about 30% faster than the FP16 X2 VAE.
Restore full Google Chrome hardware acceleration (OpenGL, WebGL, WebGPU) on legacy Mac GPUs running macOS Sequoia & Sonoma via OCLP
Python library providing GPU-accelerated tensor computation like NumPy, plus a tape-based autograd system for building deep neural networks.